Conference Agenda

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Atmospheric water vapour effects represent one of the major error sources of repeat-pass Interferometric Synthetic Aperture Radar (InSAR), and limit the accuracy of InSAR derived surface displacements. The spatio-temporal variations of atmospheric water vapour make it a challenge to measure small-amplitude surface displacements with InSAR. In previous studies, several InSAR atmospheric correction models have been successfully demonstrated: (1) Ground based correction models such as those using Global Navigation Satellite System (GNSS) observations. Such correction models are limited by the availability (and distribution) of ground observations. (2) Space based correction models including those involving NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and/or ESA Medium Resolution Imaging Spectrometer (MERIS). They are sensitive to the presence of clouds and there might be a time difference between space based water vapour and radar observations. (3) Numerical Weather Model (NWM) based correction models including those using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and/or Weather Research and Forecasting (WRF). Similar to space based correction models, there might be a time difference between NWM and radar observations. Taking into account the inherited advatanges and limitations of GNSS, MODIS and ECMWF water vapour products, we present a global and near-real-time InSAR atmospheric correction model in this paper.

Tropospheric delays can be routinely retrieved from ground based GNSS arrays in all-weather conditions and also in real-time. We develop an Iterative Tropospheric Decomposition (ITD) interpolation model that decouples the total tropospheric delays into (i) a stratified component highly correlated with topography therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. The decoupled interpolation model can then be employed to generate improved dense tropospheric delay maps compared with previsous GNSS-based models. In order to deal with areas with limited (or no) GNSS stations, we introduce the operational high resolution ECMWF (HRES-ECMWF, ~16 km), available near real-time, as well as MODIS near IR water vapour data whenever available as constrains of the ITD model, which makes the correction model globally available in all-weather conditions at any time for the first time. The applications of the ITD model to Sentinel-1 interferograms show that approximately 68%-78% of noise reduction can be achieved.

Oral presentation

The study of the artificial source signal observed by CSELF network for earthquake precursor monitoring

The first Control Source Extremely Low Frequency (CSELF) network has been built recently under the support of National Development and Reform Commission of China, which distributed in the Beijing Capital Area (BCA) and Southern Section of South North Seismic Belt (SNSB) in China for earthquake monitoring study. The network can be a part of earthquake stereoscopic monitoring system when it is combined with the satellite observation.

The network can not only receive the natural electromagnetic signal but also the artificial electromagnetic signal from the powered transmitter. A experiment of the system has been performed during 2016. The powered artificial electromagnetic signals are transmitted from 5:00 to 7:00 and from 17:00 to 19:00(GMT+8) every day. The signals at 4 different frequencies (216, 63, 12.3, 3.46 Hz) are transmitted and recorded. The natural electromagnetic signal from 1000Hz to 1000s are recorded continuously. The five electromagnetic components (North-South electric field :Ex, East-West electric field: Ey, North-South magnetic field: Hx, East-West magnetic field: Hy, and vertical magnetic field：Hz) are measured at each station of the network. The spectra of each component, impedance tensor, apparent resistivity and Impedance phase etc. are calculated using the similar software to MT data processing software. The original time series and the preliminarily processed results are transferred to the data center in the Institute of Geology, China Earthquake Administration through the CEA intranet. The further data processing and analysis are carried out in the institute for earthquake monitor study.

The artificial source electromagnetic signal is analyzed in both time and frequency domain. The adaptive filtering method was used to the raw time series data to extract the target frequency’s signal. The preliminary result showed that the amplitudes of the electromagnetic field of the artificial signals are obviously bigger than those of the natural signal. The power spectral density of the artificial signals are about 1-2 decades bigger than the natural signals for the same frequencies. The polarization characteristics of the electric and the magnetic field are studied for both source signals and the relationship between them are studied.,

In addition to the study in the feature of the artificial source electromagnetic field, we are making a tentative research on the relationship between the electromagnetic variation and the earthquake events. Some anomalies before and after Jinggu M5.9 earthquake (Dec.6, 2014) appeared in the observed data at Jinggu station for recorded natural signals. The spectrum variations appeared before and after Litang M5.1 earthquake (Sep. 23,2016) in the observed data at Jinggu station for recorded artificial signals.

Spaceborne InSAR has been a well-known established technique since the first Earth-observing SAR satellite ERS-1 was launched on 17 July 1991. Cross-track InSAR can produce a digital elevation model (DEM), and differential InSAR (DInSAR) is able to measure crustal movement and deformation caused by, for example, subsidence, landslide, earthquake, volcanic, and glacier flows. Today, Synthetic Aperture Radar (SAR) data are acquired globally from many modern satellites: Sentinel-1 operated by the European Space Agency, ALOS-2 operated by the National Space Development Agency of Japan, Radarsat-2 operated by the Canadian Space Agency, TerraSAR-X and TanDEM-X operated by the German Space Agency, and the COSMO-SkyMed constellation operated by the Italian Space Agency.

Gaofen 3 (GF-3), as a Chinese ocean surveillance satellite, was launched from the Taiyuan Satellite Launch Centre on 10 August 2016, and has been in operation since January, 2017. It carries a multi-polarized C-band SAR sensor and operates in 12 working modes, capable of imaging Earth’s surface from high-resolution (1 m) to extremely-wide-swath (650 km). The advanced technological criteria of GF-3 satellite ensure high-quality SAR images, providing an opportunity for Chinese SAR interferometry (InSAR) study.

This work aims to verify interferometric ability of the level 1 SLC data and discuss the optional InSAR processing strategy for GF-3 satellite. Sample SAR data in strip map mode were collected in Tianjin and Shanghai to the InSAR test operations, and post-processed precise orbits are used to improve the coregistration. First, the azimuth offsets between azimuth spectra sub-looking images are investigated to confirm the SLC focusing quality. Second, DEM assisted coregistration (Arikan, M., 2007) is compared with the traditional polynomial method. The DEM assisted coregistration relies on the precise orbit, and it shows better coherence for GF-3 InSAR processing even in smooth topographic areas. By comparing the GF-3 interferogram with S1A result in Shanghai, an area of about 1 x 1 km are confirmed to be subsidence. The test results verify that GF-3 SAR data are capable in InSAR application of measuring ground movements, while continuous data acquisition and near real time precise orbit are necessary for scientific and engineering application in the future.

We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China. The new TanDEM-X 12m DEM is being used to assist co - registration of all the data stacks first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; Linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract tomograms (imaging), their 3D positions and motion parameters (deformation). A progress report will be shown on these different aspects.

This work is partially supported by the CSC and UCL MAPS Dean prize through a PhD studentship at UCL-MSSL.

A 6.4-magnitude earthquake occurred near Pishan County on 3rd July, 2015. The epicenter was recorded at 37.459°N, 78.154°E, according to the USGS. The moment tensor solution from the USGS indicates that the earthquake was the result of a reverse fault rupture on a south-dipping fault (United States Geological Survey, 2015). This region is affected by the south-north converging India-Eurasia collision. The continental collision of the India and Eurasia plates is associated with a relative convergence rate of 40-50 mm/yr (Liu J. et al., 2015, Liang and Gan, 2013). Northward underthrusting of India beneath Eurasia has led to the development of the west Kunlun orogens and generates numerous earthquakes which consequently make this area one of the most seismically hazardous regions on Earth (United States Geological Survey, 2015). Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize, the seismic source parameters. Analysis of the interferograms obtained during ascending and descending orbits of the Sentinel-1A satellite in IW mode and modeling using a two-step inversion strategy suggest that this event involved thrust motion on a south-dipping fault. The best-fit slip model in the inversion suggests that the majority of the coseismic slip was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The maximum slip was ~1.2 m at a depth of ~12.5 km. The accumulative seismic moment was up to 4.5x1018 N×m, which is equivalent to a magnitude of Mw 6.4. The InSAR results supplied near-field geodetic measurements and provided independent constraints on the source parameters of this rupture.

In April 25, 2015, a strong earthquake occurred about 80 kilometers northwest of Kathmandu, the capital of Nepal. The surface wave magnitude measured by China Earthquake Network Center is Ms8.1 (http://news.ceic.ac.cn/CC20150425141126.html), and the moment magnitude calculated by the Harvard University CMT based on the focal mechanism is Mw7.9 (http://www.globalcmt.org/CMTsearch.html). And the magnitude of the Nepal earthquake is similar to that of the Wenchuan earthquake on the eastern boundary of the Tibetan Plateau in May 12, 2008. After the main shock, two aftershocks greater than magnitude seven broke out. The earthquake affected many parts of Nepal, Tibet, India, Chinese Bangladesh, Bhutan, caused a total of more than 30000 casualties. The earthquake is a thrust type earthquake that occurred in the subduction zone of Himalaya since the 8 magnitude earthquake in 1934. Most areas of Nepal are located in the mountains region of southern Himalaya. Although located on a small fault basin, the capital Kathmandu is still on the hanging wall of the Himalaya fault zone. The special terrain and geomorphic conditions cause the loss of radar coherent signal energy, which is not conducive to InSAR deformation observation. In addition, because the earthquake occurred in the heavily forested areas, in order to reduce the effect of forest on electromagnetic waves, to achieve the monitoring of surface deformation caused by the earthquake, this paper uses ALOS2/PALSAR2 dual polarization data to study. The data is the synthetic aperture radar data acquired and processed by the PALSAR-2 sensor on the ALOS-2 satellite. The working band of the sensor is L band, and the polarization of the data used in this paper is HH/HV. In this paper, we use the synthetic aperture radar differential interferometry to obtain the partial coseismic deformation field of Nepal earthquake. The results show that when the revisit period is short, InSAR technology plays an important role in the region, provide the deformation information of high signal-to-noise ratio for the earthquake. The InSAR results revealed that the Kathmandu region was strongly uplifted during the earthquake, and the area is the maximum deformation area. Corresponding to it, large surface subsidence occurred on the north side of Kathmandu, and the deformation field is consistent with the characteristics of pure thrust type earthquakes. In addition, in order to make full use of the dual polarization characteristics of the data, on the basis of obtaining the seismic deformation, this paper studies the correlation of polarization images. It is found that the intensity of polarization image changes before and after the earthquake. And we make a simple evaluation of the building damage in Kathmandu area. The results show that the extreme value of seismic deformation occurs in the west of Kathmandu City, and the low value of the correlation of polarization image also appears in the area. Therefore, there exists spatial correlation between deformation and image correlation. The correlation distribution of different polarization images is not completely consistent, perhaps because of the different degree of damage to the building. It provides a new way to detect the seismic damage of buildings by using multi polarization images.

Outward growth and associated slip partitioning of the Tibetan Plateau is always a heated spot in the geosciences field worldwide. Dalbute fault zone is a rare transpressive fault along the northern margin of the Tibet, which plays an import role in absorbing the plateau’s northward expansion. And most importantly, the middle segmentation of the Dalbute fault zone is quite close to the Karamay City (less than 30 km in distance), a very important petroleum city in the Xinjiang Province, China. Therefore, the fault zone’s seismic activity has drawn the most consideration. GPS monitoring displays that, there occurs a sudden reduce (~5-8 mm/yr) in the northward velocities of the Tibet when cutting across the NE-SE-striking Dalbute fault zone. Previous researches attribute the rate drop to the fault’s over-thrusting. Except for the crustal thickening, we notice that the strike-slip directed displacement also takes part in the Tibet’s outward growth, like absorbing the northeastward extrusion of the Junggar Basin in the northern Tian Shan range. But this speculation lacks of quantification. Besides, whether the Heshituolegai basin, Tuoli basin, Baerluker Mountain are the termination tectonics of the Dalbute fault zone still remained unclear. We plan to apply radar images provided by the Dragon project to dig into these scientific questions. We use the Small Baseline PS-InSAR technique to quantify the slip rate field, faulting segmentation, seismic activity and the possible termination structures for the Dalbute fault zone. The slip partitioning mechanism between the strike-slip and thrusting submotions will also be constrained through the help of different flying azimuth (ascending and descending) of radar satellite and the verification from the campaign and permanent GPS measurements. This study is also a meaningful exploration for slip portioning mechanism among terminus of a transpressive fault arround the Tibet. This research will also provide some useful results for the future works on protecting against and mitigating earthquake disasters in the urban areas.

Poster

Seismic Damage Recognition Based on Watershed Segmentation of SAR Image Iexture Features

Synthetic aperture radar (SAR) can penetrate clouds and haze and obtain information on ground conditions at various times of day and under different weather conditions. Since the 1950s, SAR has been widely used in the fields of surface subsidence monitoring, topographic mapping, resource exploration, environmental remote sensing and military applications, etc. In recent years, with the rapid development of SAR technology, building change detection in SAR images has become a research hotspot, especially after an earthquake. SAR technology can overcome the effects of bad weather and obtain images rapidly after earthquakes.

Information on seismic damage to buildings in SAR images from different time phases, especially in post-earthquake SAR images, is easily disturbed by other factors that affect the accuracy of information discrimination. To identify and evaluate the distribution of seismic damage accurately and make full use of the abundant texture features in the SAR image, a method for texture feature change detection in SAR images based on the watershed segmentation algorithm is proposed in this paper. We calculate the omnidirectional texture values of 8 types of texture features based on gray level co-occurrence matrices (GLCMs) .Based on the optimization of texture feature parameters, the principal components of feature parameters are segmented using the watershed segmentation algorithm, and the feature object image is obtained. Conventional methods of change detection based on texture features usually take the pixel as the calculating unit. This method introduces the concept of object orientation and carries out the calculation of the difference map at the object level. Finally, the classification threshold values for different levels of seismic damage are selected, and the identification of building damage is achieved. Using ALOS data from before and after the 2010 Yushu earthquake as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%. Compared with pixel-based methods, methods based on gray features, and methods based on single texture features, it is shown that the proposed method is effective.

The method made a breakthrough in the following ways. (1)Taking the texture feature object as the unit used in the change detection algorithm, the concept of object orientation is introduced to change detection, which represents a break from the conventional change detection methods that use the pixel as the unit.(2) The watershed segmentation algorithm is applied to texture features based on statistics, which makes the segmentation more meaningful.

Earthquake is among the most catastrophic natural disasters which seriously threat people’s lives and property. Since most of deaths and injuries in earthquakes are primarily caused by building collapse, rapid and accurate detection of collapsed buildings in urban areas is vitally important to emergency rescue and damage assessment. However, it’s often difficult to achieve suitable pre-event SAR data due to the unexpectedness and suddenness of earthquakes.

The polarimetric SAR (PolSAR) is capable of measuring the amplitude and phase of backscattered signals in four combinations of polarization. Moreover, it is sensitive to the characteristics of target like shape, size, material, structure and orientation. These make it become a potential data source to researches on building collapse extraction by using only post-earthquake SAR image. Based on this, many researches have been conducted (Li et al., 2012; Zhao et al., 2013). One issue existing is the misidentification of collapsed buildings and intact buildings which are not parallel to the SAR flight path since the scattering mechanism of the oriented intact buildings change to volume scattering dominant and reflection asymmetric. To eliminate this deficiency, the optimum polarimetric contrast enhancement (OPCE) method (Yang et al., 2000) is introduced to identify the collapsed buildings (Zhang et al., 2015). Using this method, the contrast of the intact buildings and collapsed buildings is enhanced through rotating the transmitting and receiving polarimetric antenna states. However, polarimetric information is not considered when applying this method. Yang et al. (2004) extended the OPCE method and combined it with the entropy and two polarimetric similarities, i.e. generalized optimum polarimetric contrast enhancement (GOPCE).

In this paper, we propose a new building collapse identification method based on the GOPCE method and the corresponding process framework is also presented. Moreover, the homogeneity feature of the grey level co-occurrence matrix (GLCM) is introduced to modify the GOPCE method. The case study is Yushu county where a Ms 7.1 earthquake occurred on April 14th, 2010. One post-earthquake Radasat-2 PolSAR image acquired on April 21th is utilized to test the proposed methods. By comparing with the OPCE and GOPCE methods, the GOPCE combined with homogeneity method performs better and more collapsed buildings are correctly detected. The misclassification of collapsed buildings and oriented intact buildings is also reduced. Experiments show that our proposed method can meet both time efficiency and detection accuracy requirements of earthquake rescue.

Acknowledgement

This work is supported by the Dragon 4 Cooperation Program [32244] and the National Natural Science Foundation of China [41571337].

Poster

Monitoring the activities of post-seismic geohazards in Sichuan (China) with Sentinel-1 observations

The 2008 Wenchuan earthquake resulted in thousands of geo-hazards including landslides, and debris flows. In this paper, we will attempt to use time series InSAR techniques to monitor the activities of two post-seismic geohazards, namely the Daguangbo landslide and the Wenjiagou debris flow.

Caused by the 2008 Wenchuan earthquake, the Daguangbao landslide is one of the largest landslides in the world. The whole mountaintop collapsed in the 2008 earthquake, leading to a height change up to 500 meters. TanDEM-X data is used to generate a high resolution post-seismic DEM in this paper. The high gradients of topographic errors and the decorrelation caused by vegetation in mountainous areas make the processing of Tandem-X data challenging. To solve this, we propose a re-flattening iterative method to generate a post-seismic DEM. 15 Sentinel SAR images were acquired during March 2015 to March 2016. The time series displacements of the Daguangbao landslide are obtained using our advanced InSAR TS+AEM method with the Sentinel-1 SAR images and high-resolution post-seismic TanDEM-X DEM. Four active zones are observed with a maximum displacement rate of 8 cm/year, suggesting that this landslide is still active even 8 years after the earthquake.

The Wenjiagou debris flow was the second largest landslide in the Wenchuan earthquake. The volume of the deposits is determined by comparing the post-seismic DEM derived from tandem-x data and the pre-seismic SRTM. In this site, a complex project has been set up to prevent potential debris flows by separating water and mud. Our InSAR results from Sentinel-1 observations (2015~2016) suggest that the source area of this debris flow is still active due to steep topography and rainfalls, whilst the project site and its downstream are stable. The impacts of this debris flow prevention project are to be discussed.

Poster

Mapping crustal deformation in the Red River Fault zone using InSAR

Jiajun Chen, Zhenhong Li, Peter J Clarke

COMET, School of Civil Engineering and Geosciences, Newcastle University, NE1 7RU, United Kingdom

The Red River Fault (RRF) is a major strike-slip fault running about 1000 km from southeast Tibet to South China Sea. As a result of the collision of the India and Eurasian plates, the fault is complicated, the average displacement rate is 2 to 5 mm/year and decreases from north to south. Investigation of the fault deformation information is significant to study its dynamic pattern, however, the large topography variations make it difficult to collect ground observations using GNSS.

Interferometric Synthetic Aperture Radar (InSAR), as a valued geodetic tool, has been applied in mapping crustal deformation at the scale of hundreds of kilometres with a high spatial resolution (e.g. a few metres to tens of metres) over the past two decades. Sentinel-1A was launched in April 2014, Sentinel-1B in April 2016 and both have been collecting data routinely. In the RRF zone, Sentinel-1 data are being acquired every 12/24 days with both satellites. The small temporal baseline, together with small spatial baselines (i.e. orbital separations) greatly improve interferometric coherence at C-band. In addition, Sentinel-1 images cover a wide footprint, 250 km from near to far range in Interferometric Wide Swath (TOPS) mode. Since October 2014, there have been over 400 Sentinel-1 images collected from 4 descending and 3 ascending tracks covering the RRF zone. Also, over 1500 ALOS-1 images collected between 2007 and 2011 are available in this region, and ALOS-2 data are being systematically acquired since 2014. The long wavelength (L-band) of ALOS-1/2 ensures good coherence. All the above-mentioned factors make it now possible to use InSAR to monitor slow-slip crustal deformation in this region.

The SAR data are interferometrically processed using our automatic processing chain based on the InSAR Scientific Computing Environment (ISCE) software. The variable climate in RRF zone challenges InSAR observing and processing, we calibrate the interferograms for atmospheric water vapour using high-resolution ECMWF products. Finally, time series analysis is performed to determine the interseismic deformation rate of the RRF using the in-house InSAR time series inversion package (InSAR TS + AEM, Li et al. 2009). It includes an advanced network correction approach for residual orbital correction and an atmospheric phase screen estimation with a priori deformation model. The InSAR measurements will be discussed to implicate future seismic hazard in the RRF zone.

Evaluating the use of sub-Pixel Offset Tracking cf. dInSAR using TerraSAR-X Staring Spotlight data for monitoring landslides in the Three Gorges Region of China

Luyi Sun, Jan-Peter Muller

Mullard Space Science Laboratory, University College London, United Kingdom

Conventional dInSAR techniques have been frequently used in the past for deformation mapping including the mapping of landslide activities. However, several difficulties arise when attempting to apply dInSAR in areas with steep slopes and rugged topography, high humidity and dense vegetation cover such as over the Three Gorges Region. In addition to these difficulties, it is shown that the maximum detectable displacement gradient of dInSAR can be exceeded in our case study area even when using the highest resolution TerraSAR-X data.

A sub-Pixel Offset Tracking approach (sPOT) is applied to monitor slow-moving landslides in densely vegetated and steep terrain. This approach is shown of being capable of measuring centimetre-level landslide rates by using natural scatterers in densely vegetated terrain in line with measurements derived from corner reflectors.

The potential and limitations of TSX-ST (TerraSAR-X Staring Spotlight) data on measuring surface deformation using dInSAR and offset tracking techniques are assessed through case studies on the southern banks of the Yangtze River, in particular whether the improvement of the resolution of Staring Spotlight mode helps to address some of the issues that were encountered previously.

In addition, we show how the TanDEM-X Coregistered Single look Slant range Complex (TDX CoSSC) data can be employed to produce a 6 m resolution DEM. The impact of using different sources of DEMs is then assessed on deformation measurements via offset tracking and dInSAR.

This work was partially supported by the China Scholarship Council (CSC) and UCL through a PhD studentship at UCL-MSSL.

Poster

A Comparison of InSAR Time Series Approaches for Monitoring Wide-Scale, Low-Magnitude Ground Surface Deformation

Julia Stockamp1,2, Zhenhong Li2

1School of Geographical and Earth Sciences, University of Glasgow, United Kingdom; 2COMET, School of Civil Engineering and Geosciences, Newcastle University, United Kingdom

For decades, crustal motion and surface deformation processes have been investigated with differential SAR Interferometry. This geodetic technique can lead to very good estimations of ground movement, when applied to co- and interseismic processes, land subsidence phenomena, landslides or volcanic motion with significant deformation magnitudes. However, its application still presents a challenge considering wide-scale, subtle ground movement that is hardly measurable with InSAR in the presence of often indistinguishable orbital, atmospheric or topographic noise.

Different SAR sensors such as ESA’s ERS-1/2, ESA’s Envisat ASAR, ESA’s Sentinel-1 and JAXA’s ALOS PALSAR are tested in this study to assess their capability to achieve the required accuracy in the interferometric phase for monitoring slow, low magnitude surface movements (in the low mm-level). This applies to, for example, observations of glacial isostatic uplift, interseismic strain accumulation or small subsidence processes.

The range of possible error sources, such as residual orbital artefacts or atmospheric water vapour, require to be addressed in order to allow the extraction of any subtle deformation signals. Their elimination from interferograms present the biggest challenge due to their ‘masking’ characteristic.

This study advances currently known time series inversion methods for deformation monitoring and mapping of natural hazards. Results from two InSAR time series approaches are compared. On the one hand, this comprises an improved time series inversion package developed at the University of Glasgow and Newcastle University (“InSAR TS+AEM”, Li et al. 2009), based on the more classical and well established Small Baseline approach. This includes an advanced network correction approach for residual orbital effects and an atmospheric phase screen estimation with an a priori deformation model. On the other hand, a new technique is tested for reducing image artefacts and to derive a time series from InSAR data: A combined approach of Principal Component Analysis and Independent Component Analysis aims to separate the desired ground deformation signal from unwanted noise in interferograms. The idea is to take advantage of the signals’ different spatial and temporal characteristics and to decompose the mixtures into statistically independent components in space and time to filter out geophysical deformation.

Damxung area is the place where strong earthquakes happen frequently, and the former studies have shown that there is a close relationship between strong earthquakes and active faults in this place, so it is necessary for us to study the distribution, geometric structure and motion characteristics of the faults if we want to know the initiation mechanism and seismogenic environment of the earthquakes. In this paper, by using a wide range of remote sensing data such as Landsat-7 ETM+, ALOS, GF-2, Sentinel-1 and DEM data, and utilizing a wide variety of image enhancement technology such as multiband color composite, PCA and ratio analysis based on these data, active fault information was extracted and the remote sensing interpretation marks about active faults were established, and finally, we displayed the the distribution and activity of the Yadong-Gulu fault and the Jiali fault in the study area. Our results have shown that: the Yadong-Gulu fault mainly consisted of normal faults and strike slip faults, and it could be divided into three parts. The north part of the Yadong-Gulu fault had direction toward NNE with part of it buried, and normal faults developed associating with strike slip faults. The middle part of the Yadong-Gulu fault had direction toward NE, and the fault was exposed, and the main faults of it were sinistral strike-slip normal faults. The south part of the Yadong-Gulu fault had a direction toward NNE, which then changed to NS on south, and the fault was partly buried with many secondary faults around it, and it mainly consisted of dextral strike-slip normal faults which had formed many graben basins. The Jiali fault was buried partly in the study area and could be divided into two branches, and it was dextral strike-slip normal fault. The wide existence of fault triangular facet, pull-apart basin and river break in the remote sensing images revealed that this area had a tectonic background characterizing by stretch and twist, which was mainly governed by upwelling movement on vertical direction and extension movement on horizontal direction of the middle Tibetan Plateau which was caused by the subduction of the India Plate. The remote sensing interpretation in this paper reflected the current characteristics of faults’ activities in the study area, and the characteristics of these activities had a close relationship with the earthquakes. What’s more, the results of this study also showed that enhancement processing upon remote sensing image could highlight some specific landforms and geological structure information, and the remote sensing image had unparalleled advantages compared with field geological investigation, and remote sensing technology had a bright prospect in geological investigation and geological disaster monitoring.

Poster

Detection of surface deformation field of small earthquakes by InSAR technique

Abstract: The Qinghai Tibet Plateau is the world's youngest and most active plateau, due to the collision between the India plate and the Asian plate led to most of the region's fault zone is active, a lot of small earthquakes between Mw5.0 and Mw6.0 occurred every year, these small earthquakes can cause ground subsidence, influence in fault state. Based on the ENVISAT satellite data, the surface deformation caused by small Tibet earthquake were analyzed obtain the coseismic deformation field, comparative analysis the surrounding areas of land subsidence caused by the small earthquakes, and use the GPS data to verify, results showed that there was high consistency between the SAR data acquisition deformation and GPS measurement result.

The Qinghai Tibet Plateau is the world's youngest and most active plateau, with an average altitude of more than 5000 m, the main structural features currently are the results of the India plate and the Asian plate collision since the 50-60Ma. Because the impact time is new, tectonic collision and orogeny of the intact are save well, and many continental dynamic process after collision are continues, so the Tibetan Plateau is the most ideal place for the new structure research.

Qinghai Tibet Plateau is a strongly rising block surrounded by the surrounding active faults. The surrounding fracture surface tend to plateau interior, thus formed in the mountains around the edge of the plateau to plateau lowland obduction "coronary morphology structure". The type of peripheral plateau active tectonics dominated by fracture structure, its basic characteristics are the reverse fault internal fault dip plateau. The southern boundary of the Tibetan Plateau is the main boundary fault zone in Himalaya, the west adjacent to the Yika La Kunlun fault zone and the Pamir Plateau; the northern boundary along the northern margin of West Kunlun fault zone, the Altun fault and the northern margin of Qilian Mountains fault zone, curving to six mountain fault zone; the Eastern boundary along the Longmen Mountain Fault Zone, An’ninghe fault and Xiaojiang Fault with the extension of the twists and turns.

Select the Lhasa block as the study area, analysis the surface deformation of Mw5.0~6.0 earthquake in the study area, using the traditional two track difference method for data processing, the basic idea is to generate two pass interference using two images before and after of the surface change experimentation area, topographic information removed from the interferogram. Then can get the deformation information. The basic process is needed before the earthquake and after the earthquake SAR data and DEM data, the data before the earthquake as the main image formed interferogram with the post earthquake data, simulated interferogram using DEM, the simulated interferogram is subtracted from the interferogram by SAR data, then form the differential interferogram. The advantage of this method is that it does not need the phase unwrapping of the interferogram to avoid the difficulty of understanding, but also can obtain the precision of the deformation results.

2. research significance

The Qinghai Tibet Plateau is an earthquake prone area, especially some small earthquakes (Mw5.0~6.0). These earthquakes release the earth's crust stress, reduce the probability of strong earthquakes in the fault, and effectively alleviate the seismic risk in the region. At the same time, through the study of the mechanism of the occurrence of small earthquakes, we can obtain the geophysical parameters. It provides valuable information for the assessment of regional seismic hazard.

Study on deformation field of small earthquakes in Lhasa block since 90s of last century using InSAR technique. In March 24, 2010 the Tibet area (N32.51 degrees, E92.83 degrees) a Mw5.6 earthquake as an example, using the traditional differential method pass interference to obtain the coseismic deformation field of the earthquake, coseismic interferograms obtained using multiple sets of different seismic data, through data analysis to obtain the coseismic displacement of the interferometric phase, clear surface displacement caused by the earthquake. At the same time, the use of GPS data to verify the accuracy of the result, inverse the fault parameters based on coseismic deformation field and GPS data, to obtained the detailed parameters of fault, which can provide the basis for the subsequent study of fault and the mechanism of earthquake.

This work will report the studies undertaken in the past year, which is aimed to developing viable methods and techniques for detecting anomalies from space and terrestrial electromagnetic data that are observed by the SWARM satellite and the network of the Control Source Extremely Low Frequency (CSELF) in China and investigating the correlation between anomalies and earthquakes. We have developed an effective algorithm for detecting anomalies from time series data and evaluated them over benchmark datasets, as well as preliminarily on electromagnetic data observed by the Swarm satellites and by the CSELF. We will present a number of issues related to the Swarm satellite data, the methods required to process the data, and finally present a comparative case study of the Jingpu earthquake using the Swarm and CSELF data.